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Numerical Analysis (CS 450) Spring 2024

What Where
Time/place Tue/Thu 11:00am--12:15pm [1404 Siebel Center]
Class URL https://relate.cs.illinois.edu/cs450-s24
Class recordings https://mediaspace.illinois.edu/channel/channelid/330048022
Web forum https://piazza.com/illinois/spring2024/cs450
Calendar View Calendar »

Quizzes

Posted here by start of each lecture. Due 7 days from start of lecture, Generally, we will go over all or most quiz questions during the lecture.

Quiz 1: Error, Conditioning, and Course Policies »

Quiz 2: Floating Point Arithmetic »

Quiz 3: Matrix Norms and Conditioning, Triangular Systems »

Quiz 4: Solving Linear Systems »

Quiz 5: Solving Linear Least Squares Problems »

Quiz 6: Linear Least Squares Problems and Low-Rank Approximation »

Quiz 7: Eigenvalues, Conditioning, and Power Iteration »

Quiz 8: Eigenvalue Decomposition Algorithms »

Quiz 9: Nonlinear Equations »

Quiz 10: Nonlinear Optimization »

Quiz 11: Constrained Nonlinear Optimization »

Homework

Homework 1 »

Homework 2 »

Homework 3 »

Homework 4 »

4-Credit Hour Homeworks

For the 4-credit hour section, addendum problems are worth 1/4 of the total credit for each assignment. For the 3-credit hour section, these problems may be completed for extra credit, with half of the value (1/6 of the assignment value).

Homework 1 Addendum »

Homework 2 Addendum »

Homework 3 Addendum »

Course Outline

Team

Edgar Solomonik

Edgar Solomonik

(Instructor)

Email: solomon2@illinois.edu

Office: Siebel 4229, Wenesday 1 pm


Nicolas Nytko

Nicolas Nytko

(TA)

Email: nnytko2@illinois.edu

Office: Siebel 4th floor atrium (outside 4102), Monday/Wednesday 2-3pm


Jiakun Yan

Jiakun Yan

(TA)

Email: jiakuny3@illinois.edu

Office: Siebel 0209, Tuesday 3-4pm, Thursday 2:20-3:20pm


Jize Jiang

Jize Jiang

(TA)

Email: jizej2@illinois.edu

Office: Siebel 0207, Wednesday/Friday 10-11am


Statement on CS CARES, Values, and Code of Conduct

All members of the Illinois Computer Science department---faculty, staff, and students---are expected to adhere to the CS Values and Code of Conduct. The CS CARES Committee is available to serve as a resource to help people who are concerned about or experience a potential violation of the Code. If you experience such issues, please contact the CS CARES Committee. The instructor of this course are also available for issues related to this class.

Textbook


Scientific Computing: An Introductory Survey
Scientific Computing: An Introductory Survey / E-Book (accessible free of charge from campus network/VPN)

Michael T. Heath, Revised Second Edition, Society for Industrial and Applied Mathematics

Resource site

Also see our class Piazza forum for a discount code for purchasing the book from SIAM.


Computing

We will be using Python with the libraries numpy, scipy and matplotlib for in-class work and assignments. No other languages are permitted. Python has a very gentle learning curve, so you should feel at home even if you've never done any work in Python.

Running Code on your Own Computer

While running code in this online system should technically suffice to do your work for this class, you may find it useful to also install Python on your own computer.

The recommended and perhaps one of the easier ways of doing so involves downloading the Anaconda Python distribution. Note that this is a commercial product (even if it is free of charge), and this is not intended as an endorsement of the company or the product. Note that we cannot promise to provide technical support for this installation.

Download Anaconda Python »

Another way to obtain a Python installation is through a virtual machine image:

Download Virtual Machine »

Grading Policies

View policies »

Python Help

(see section 1 of the outline for more)

Python workshop material

Numpy Help

(see section 1 of the outline for more)